Getting Started with AI

See what the Splunk AI Assistant can do for you https://youtu.be/ynRBiepXVw4?si=eua38GwP0nwuvk3m

The Splunk App for Anomaly Detection finds anomalies in time series datasets and provides an end-to-end workflow to manage and operationalize anomaly detection tasks. The app detects seasonal patterns and finds anomalies in just a couple of clicks.

* Description * Smart Alerts Assistant for Splunk (beta) enables analysts to focus on the most important and highest-priority issues. Under the hood, Smart Alerts Assistant for Splunk captures user feedback to improve prioritization and uses machine learning to output a recommended, stack-ranked priority for each alert. Smart Alerts Assistant for Splunk empowers customers to optimize their operations centers and focus on top priorities instead of spending time triaging alerts.

The Splunk AI Toolkit delivers new SPL commands, custom visualizations, assistants, and examples to explore a variety of ML concepts.

This add-on contains a Python interpreter bundled with the following scientific and machine learning libraries: numpy, scipy, pandas, scikit-learn, and statsmodels. With this add-on, you can import these powerful libraries in your own custom search commands, custom rest endpoints, modular inputs, and so forth.

This add-on contains a Python interpreter bundled with the following scientific and machine learning libraries: numpy, scipy, pandas, scikit-learn, and statsmodels. With this add-on, you can import these powerful libraries in your own custom search commands, custom rest endpoints, modular inputs, and so forth.

This add-on contains a Python interpreter bundled with the following scientific and machine learning libraries: numpy, scipy, pandas, scikit-learn, and statsmodels. With this add-on, you can import these powerful libraries in your own custom search commands, custom rest endpoints, modular inputs, and so forth.

The Splunk App for Data Science and Deep Learning (DSDL), formerly known as the Deep Learning Toolkit (DLTK), lets you integrate advanced custom machine learning and deep learning systems with the Splunk platform. DSDL extends the Splunk AI Toolkit (AITK), formerly known as the Machine Learning Toolkit (MLTK), with prebuilt Docker containers for TensorFlow, PyTorch, and a collection of data science, NLP, machine learning and advanced AI libraries. By using predefined workflows for rapid development with Jupyter Lab Notebooks, DSDL enables you to build, test, and operationalize your custom AI models with Splunk. You can leverage GPUs for compute intense training tasks or LLM inference and flexibly deploy models on CPU or GPU enabled containers. The app ships with 40+ examples that showcase different artificial intelligence, deep learning and machine learning algorithms for classification, regression, forecasting, clustering, graph analytics, and natural language processing tasks. Learn from these examples to tackle your most advanced data science and custom AI use cases in the areas of IT Operations, Security, Application Development, IoT, Business Analytics, and beyond.